Diffraction Modeling for Improved 3DMA GNSS Urban Navigation

authored by
Anat Schaper, Fabian Ruwisch, Steffen Schön
Abstract

Positioning with Global Navigation Satellite Systems (GNSS) in urban areas is still a challenging task. Obstacles in the vicinity of the antenna may block the Line-of-Sight (LOS) ray or degrade the signal resulting in lower signal strengths, signal interruptions and extra path delays of the signal. Ray tracing algorithms are therefore a commonly used 3D map aided (3DMA) approach to detect signals affected by the environment. Unlike signal reflection, diffraction is rarely considered as error source. A commonly used approach to mitigate the influence of diffracted signals on the position solution is the weighting of observations based on their Carrier-to-Noise Power Density Ratio (C/N0), e.g. by the SIGMA-ε model. However, in the case of diffraction of a LOS signal, the signal can be amplified, although the quality of the observation has decreased. Consequently, the C/N0 does not always provide reliable information about the quality of the signal. In this contribution, we present a detailed study of the behavior of diffraction in urban areas based on a Level of Detail (LoD)2 building model. A new layer is added to the existing classes of LOS, multipath (MP), Non-Line-of-Sight (NLOS) and blocked as well as the received signal strength is predicted. We validate our algorithm by both simulations and real data in static and kinematic scenarios. We show that diffraction affects all types of signal classes, resulting in extra path delays in cm-range and a loss in signal strength of up to 17 dB-Hz. Finally, an adapted weighting scheme is developed combining the SIGMA-ε model with ray tracing and diffraction modeling information. Its performance is tested in multi-GNSS Single Point Positioning (SPP) in a kinematic scenario in the city of Hannover. Our adapted weighting scheme delivers significant benefits in both 3D and 2D accuracy compared to the conventional SIGMA-ε weighting. In urban trenches, combining the 8-class model with the C/N0 dependent SIGMA-ε model results in reductions of the RMSE of up to 20 %. Large outliers in the positioning solution, especially for user positions in narrow urban trenches, could be drastically reduced using the combined weighting scheme.

Organisation(s)
Institute of Geodesy
Type
Conference contribution
Pages
1902-1916
No. of pages
15
Publication date
2022
Publication status
Published
Peer reviewed
Yes
Electronic version(s)
https://doi.org/10.33012/2022.18541 (Access: Closed)
 

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